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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

An Inquiry Into the Effects of Statutory Climate on the Political Attitudes and Behavior of State-Level Public Administrators

Snead, John David 24 February 2000 (has links)
This dissertation examines ways in which differences in states' political activity laws affect the political attitudes and reported behavior of senior state government employees. Of particular concern is whether a stringent little Hatch Act engenders any "chilling effects" that may lead these workers to shy away from permissible political activities. The study included officials employed in Pennsylvania, which has a restrictive political activity statute, and New Jersey, which has generally permissive laws. Mail questionnaires were sent to 962 officials, 512 from Pennsylvania and 450 from New Jersey. Responses were received from 582 employees, yielding a 61.91% response rate. Compared to New Jersey officials, those from Pennsylvania were less knowledgeable about their state's political activity laws. The Pennsylvania employees also reported being less politically active and less satisfied with their activity, and were more likely to indicate that they would increase their level of political activity if state prohibitions were eliminated. However, compared to their New Jersey counterparts, these officials were no less inclined to engage in permissible political activities. This finding casts doubt on the notion that a highly restrictive statutory climate spawns chilling effects. / Ph. D.
2

I Datamäklarens Nät : Om massiv datainsamling och dess effekt påIT-användning

Hallenquist, Peter January 2017 (has links)
The aim of this   study is to investigate whether IT users with a reasonable awareness of data   gathering, in the context of Big Data, perceive this data gathering as a   threat to their privacy and if they take steps to counteract it. Building   upon previous research, such steps are assumed to be either ”active” or   ”passive”. Active measures serve to hide data or obscure its contents from   those who would collect it, for example by using a VPN (Virtual Private   Network) or fake aliases, while passive methods might consist of avoiding to   speak out on certain topics or seek out information that may be deemed   suspicious. Based largely on the Theory of Reasoned Action a theoretical   model has been developed to investigate whether a correlation can be seen   between beliefs about data gathering as a privacy threat and the intention to   protect oneself from this threat. To this aim a survey was given to   university students at programmes closely related to IT, as they would likely   have a good understanding of the subject at hand and would be well equipped   to answer the survey´s questions. The results show that almost all of the respondents   see Big Data related data gathering as a threat to privacy and the majority   see themselves likely, to varying degrees, to take measures to protect   themselves. The data shows a reasonable, though weak, correlation between   this view of data gathering as a privacy threat and the tendency towards   self-protection. Further, there is a clear preference towards active   measures, though this may in part be a consequence of the respondents'   aptitude for IT. Further research should be done to investigate the prevalence   of the view of data gathering as a privacy threat in society at large, and   the extent to which it results in self-protective behaviour such as self   censorship. Additionally, the theoretical model developed for this study   should be further developed and tested so that it may be of use in future   studies on data gathering and its effect on IT users. / Denna studie ämnar utreda om IT-användare med en   viss medvetenhet om Big Data-relaterad datainsamling ser denna som ett hot   mot sin personliga integritet och om de då tar steg för att skydda sig från   detta hot. Baserat på tidigare forskning har två typer av   integritetsskyddande åtgärder identifierats: ”aktiva” och ”passiva”. Aktiva   åtgärder är sådana som syftar till att dölja eller otydliggöra data för den   som samlar in dem, exempelvis genom att använda en VPN (Virtual Private   Network) eller falska alias, medan passiva åtgärder kan gå ut på att undvika   att uttala sig om vissa saker eller söka ut information om suspekta ämnen. En   teoretisk modell, baserad till stor del på Theory of Reasoned Action, har   utvecklats för att undersöka om ett samband finns mellan övertygelser om   datainsamling som integritetshot och avsikten att skydda sig från detta. I   detta syfte har en enkätundersökning skickats ut till studenter på   universitetsprogram med stark IT-anknytning, då dessa antas ha en god   förståelse för undersökningens ämnesområde och bör vara väl rustade att svara   på dess frågor. Resultatet visar att nästan alla av respondenterna ser Big   Data-relaterad datainsamling som ett hot mot den personliga integriteten och   de flesta kan se sig själva, till varierande grad, ta steg för att skydda sig   från detta hot. Man kan se en rimlig, om än svag, korrelation mellan denna   syn på datainsamling som integritetshot och avsikten gentemot   integritetsskyddande beteende. Vidare kan man se en klar preferens för aktiva   åtgärder, vilket delvis kan ha att göra med respondenternas förmodade höga   IT-kunnande. Ett område för framtida forskning är hur utbredd synen på   datainsamling som integritetshot är i samhället i stort och i vilken   omfattning den ger upphov till integritetsskyddande beteende såsom   självcensur. Däröver bör den teoretiska modell som utvecklats för denna   studie ytterligare förbättras och testas, så att den kan användas som ett   verktyg i vidare forskning kring datainsamling och dess inverkan på   IT-användare.

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